class_docstr: ScipyDistance class extends VectorizedDistance for the use of Scipy's vectorized distances.
  
  This class uses `scipy.spatial.distance.cdist` to calculate distances between two `np.ndarray`.
  
  Parameters
  ----------
  metric : str, optional
      Defines the specific Scipy metric to use to calculate the pairwise distances between
      new candidates and objects.
  
  Other kwargs are passed through to cdist
  
  See Also
  --------
  [`scipy.spatial.distance.cdist`](https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.cdist.html)
code: def __init__(self, metric: str = "euclidean", **kwargs):
      self.metric = metric
      super().__init__(
          distance_function=partial(cdist, metric=self.metric, **kwargs)
      )
  
imports: from abc import ABC, abstractmethod
  from functools import partial
  from logging import warning
  from typing import TYPE_CHECKING, Callable, List, Optional, Sequence, Union
  import numpy
  from scipy.spatial.distance import cdist
label_desc: Use image node_id 1 to create a new ScipyDistance object from inherited base classes: VectorizedDistance with example: obj = ScipyDistance(metric)